Smart buildings start-up Verdigris raises $6.7 million in funding

California-based start-up Verdigris has raised $6.7 million in a latest round of funding, bringing its total funding to $16 million to date. The firm’s sensors and AI-powered IoT platform are used to make buildings more efficient.

The firm’s software produces reports including energy forecasts, alerts about faulty equipment, maintenance reminders, and energy usage information for each and every device and appliance. The company’s suite of applications gives building engineers an overview, an “itemized utility bill”, reporting, and automation tools for their facility. To date, Verdigris counts Autodesk, Honeywell, Hyat Hotels, Intercontinental Hotels and Marriott among its customers.

The artificial intelligence (AI) company said this latest round of funding was led by Jabil, a current customer, Verizon Ventures, Stanford StartX Fund, and existing angel investors. The money will be used to scale manufacturing and customer operations in a bid to meet growing customer demand and assistance with product rollouts, it said.

The announcement comes after Verdigris recently launched Einstein, a smart sensor and metering solution that supposedly reduces energy consumption and cost for large buildings. It works by using a myriad of sensors that wirelessly stream data from a building’s electrical panel into the cloud where Verdigris’ AI analyses and makes sense of the ‘electrical “fingerprints”.’

For customers, this should mean gaining access to smart and more responsive building operations, with Verdigris’ AI able to predict future breakdowns, assess energy wastage and send customers important information about energy consumption right ‘down to the device.’ In short, it should help customers to save money on energy costs.

Verdigris wants you to ‘have conversations’ with buildings

Speaking to VentureBeat about the Einstein product, Verdigris CEO Mark Chung, and said: “Rather than take a big data approach where we study thousands of motors and this is the failure pattern, we instead take a physics based model which is looking at a signal through our sensors. We’ll then build a physics-based machine learning algorithm to look for that pattern, not the anomaly.”

“If you have a building management system, the data from our platform will feed into that building management system and make the building run more efficiently,” Chung said. “The machine failure detection is more targeted toward operational savings or top line savings like reputation, so if it’s a factory it’s more operational. If it’s a hotel it’s reducing calls about hot or cold rooms.”

“What we’re trying to do for buildings and making buildings smarter is a lot like what natural language processors [have done to make] conversations easier to have. We want to create an artificial intelligence that powers all the buildings in the world and allows you to have conversations with those buildings,” Chung concluded.

Jabil EVP strategic planning and development, Joe McGee, commented: “Verdigris has allowed us to much better understand the drivers of our energy consumption and how we can minimize our demand.”

Jabil said it plans to roll out Verdigris’ platform in a number of its manufacturing sites and then, if successful, across its entire portfolio.

As well as its numerous clients in the hospitality sector, Verdigris currently has a partnership with NASA’s Sustainability Base to research the platform’s potential for future habitat design and predictive analytics to reduce failure on future missions to outer space.